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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Field validation of data-driven BSDF and peak extraction models for light-scattering fabric shades

Shading and daylighting systems affect cooling, heating, and lighting energy use by modulating solar radiation through the building façade. Characterizing shading systems holistically and accurately helps designers and engineers evaluate shading systems to achieve energy and non-energy performance goals. These complex fenestration systems can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident radiation to hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during the raytracing calculation. A peak extraction (PE) algorithm was developed to circumvent limits in BSDF angular resolution, where the specular peak is extracted during simulation by evaluating the BSDF in the through direction and surrounding region. The objective of this study was to validate this measurement and modeling workflow using field monitored data from a full scale testbed with eleven installed fabrics of different weaves, openness factors, and colors and assess the accuracy of the workflow under different adaptation and contrast conditions. Test conditions were limited to clear sky conditions with the sun in the field of view. Results showed that, for tensor tree datasets, vertical illuminance, solar luminance (2.5° apex), and daylight glare probability (DGP) were predicted to within a mean bias error (MBE) error of -456 lx (-12.3%), -3.46e5 (-38.4%), and -0.042 (-7.8%) when full PE occurred. With a binary classification of glare/ no glare, DGP was predicted accurately with a true positive rate of 0.98 and true negative rate of 1.0 using tensor tree data and less accurately with Klems BSDF data, particularly for cases of no glare. The workflow may be of insufficient accuracy to distinguish borderline performance between fabrics using the four-point glare scale, particularly under low adaptation, high contrast daylit conditions. Errors were due to reductions in peak shape and intensity across the BSDF interpolation and data reduction workflow. Future work is needed to better preserve measurement fidelity during interpolation and sampling, which in turn will improve PE performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Improving Traditional Registrational Trial End Points: Development and Application of a Desirability of Outcome Ranking End Point for Complicated Urinary Tract Infection Clinical Trials

Abstract Background Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. Methods Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. Results In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. Conclusions DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.

Immunology↗
DOE OSTI2021

Competition within low-density bacterial populations as an unexpected factor regulating carbon decomposition in bulk soil

Bacterial decomposition of organic matter in soils is generally believed to be mainly controlled by the access bacteria have to organic substrate. The influence of bacterial traits on this control has, however, received little attention. Using the substrate-dependent Monod growth model, we develop a bioreactive transport model to screen the interactive impacts of spatial dispersion and bacterial traits on mineralization. Bacterial traits primarily involved in the bacterial response to the substrate concentration, such as the maximum specific uptake rate and efficiency, the adaptation time of the uptake rate and the initial population density, are considered. We compare the model results with two sets of previously performed cm-scale soil-core experiments in which the mineralization of the pesticide 2,4-D was measured under well-controlled initial distributions and transport conditions. Bacterial dispersion away from the initial substrate location induced a significant increase in 2,4-D mineralization. Additionally, it reveals an increase of specific uptake rates at lower bacterial densities, more than compensating the decrease of specific uptake rates caused by substrate dilution. This regulation of bacterial activities by density, caused by the local depletion of substrate by competing bacteria, becomes dominant for bacteria with an efficient uptake of substrate at low substrate concentrations (a common feature of oligotrophs). Such oligotrophs, commonly found in soils, compete with each other for substrate even at remarkably low population densities. The ratio-dependent Contois growth model, which includes a density regulation in the expression of the uptake efficiency, is more accurate and convenient to calibrate than the substrate-dependent Monod model, at least under these conditions. In view of their strong interactions, bioreactive and transport processes cannot be handled independently but should be integrated, in particular when reactive processes of interest are carried out by oligotrophs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Unmixing Symmetries

The low-lying spectra of atomic nuclei display diverse behaviors, for example, rotational bands, which can be described phenomenologically by simple symmetry groups such as spatial SU(3). This leads to the idea of dynamical symmetry, where the Hamiltonian commutes with the Casimir operator(s) of a group, and is block diagonal in subspaces defined by the group’s irreducible representations or irreps. Detailed microscopic calculations, however, show these symmetries are in fact often strongly mixed and the wave function fragmented across many irreps. More commonly, the fragmentation across members of a band are similar, which is called a quasidynamical symmetry. In this Letter I explicitly, albeit numerically, construct unitary transformations from a quasidynamical symmetry to a dynamical symmetry, adapting the similarity renormalization group (SRG) in order to transform away the symmetry-mixing parts of the Hamiltonian. In this work, the standard SRG produces unsatisfactory results, forcing the induced dynamical symmetry to be dominated by high-weight irreps irrespective of the original decomposition. Using spectral distribution theory to rederive and diagnose standard SRG, I introduce a new form of SRG. The new SRG transforms a quasidynamical symmetry to a dynamical symmetry, that is, unmixes the mixed symmetries, with intuitively more appealing results.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Nonlinear Virtual Inertia Control of WTGs for Enhancing Primary Frequency Response and Suppressing Drivetrain Torsional Oscillations

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce drivetrain torsional oscillations of WTGs. This paper addresses this issue and develops a novel nonlinear VIC based on objective holographic feedback theory and the definition of a completely controllable system of Brunovsky type. Simulation results under various scenarios demonstrate that the proposed technique outperforms existing VICs in terms of enhancement of system frequency nadir, suppression of WTG drivetrain torsional oscillations, fast and smooth recovery of WTG rotor speed to the original maximum power point (MPP) before the disturbance as well as preventing secondary frequency dip caused by traditional VIC. The proposed technique is also able to adaptively coordinate multiple WTGs to enhance the frequency support and the dynamic performance of each WTG.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Redefining Resource Adequacy for Modern Power Systems: A Report of the Redefining Resource Adequacy Task Force

Today's rapidly increasing levels of wind, solar, storage, and load flexibility require the industry to rethink reliability planning and resource adequacy methods for modern power systems. Periods with a risk of shortfall often no longer coincide with peak demand - reliability risks are less about peak load and more about the daily setting of the sun, extended cloud cover, wind speeds, cold snaps, and heat waves. In addition, demand is increasingly flexible. Key resources are time-sensitive, as batteries need time to recharge and electricity customers can only be asked to provide demand response for just so long. And reliability failures are often correlated - with one another and with the weather. Two driving factors require the industry to reconsider its analytical approach for resource adequacy: (1) Chronological grid operations: The increasing importance of variable renewable resources (such as wind and solar) and of energy-limited resources (storage and demand response) make it essential to understand the full year of chronological operation of the grid. Specific attention must be paid to hourly, seasonal, and inter-annual resource variability. The sequence of the variability is key, as energy-limited resources such as batteries or demand response require either a preceding period or subsequent period of high production to be useful for grid reliability. (2) Correlated events: Historically, resource adequacy analysis focused on shortfalls caused by random, discrete mechanical failures of large generating units. In contrast, shortfalls today are often caused by multiple, correlated events caused by common weather patterns. Resource adequacy analysis must increasingly shift its focus to these correlated events. The redesign of resource adequacy methods will benefit from a set of guiding principles to better allow for sharing of insights and best practices, interregional resource coordination, and a smoother regulatory process for resource procurement. The objective of this report is to move this redesign forward. It provides an overview of key drivers changing the way resource adequacy needs to be evaluated, identifies shortcomings of conventional approaches, and outlines first principles for practitioners to consider as they adapt their approaches. The central message is: what got us here won't get us there.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Genome-Wide Analysis of Terpene Synthase Gene Family in Mentha longifolia and Catalytic Activity Analysis of a Single Terpene Synthase

Terpenoids are a wide variety of natural products and terpene synthase (TPS) plays a key role in the biosynthesis of terpenoids. Mentha plants are rich in essential oils, whose main components are terpenoids, and their biosynthetic pathways have been basically elucidated. However, there is a lack of systematic identification and study of TPS in Mentha plants. In this work, we genome-widely identified and analyzed the TPS gene family in Mentha longifolia, a model plant for functional genomic research in the genus Mentha. A total of 63 TPS genes were identified in the M. longifolia genome sequence assembly, which could be divided into six subfamilies. The TPS-b subfamily had the largest number of genes, which might be related to the abundant monoterpenoids in Mentha plants. The TPS-e subfamily had 18 members and showed a significant species-specific expansion compared with other sequenced Lamiaceae plant species. The 63 TPS genes could be mapped to nine scaffolds of the M. longifolia genome sequence assembly and the distribution of these genes is uneven. Tandem duplicates and fragment duplicates contributed greatly to the increase in the number of TPS genes in M. longifolia. The conserved motifs (RR(X)8W, NSE/DTE, RXR, and DDXXD) were analyzed in M. longifolia TPSs, and significant differentiation was found between different subfamilies. Adaptive evolution analysis showed that M. longifolia TPSs were subjected to purifying selection after the species-specific expansion, and some amino acid residues under positive selection were identified. Furthermore, we also cloned and analyzed the catalytic activity of a single terpene synthase, MlongTPS29, which belongs to the TPS-b subfamily. MlongTPS29 could encode a limonene synthase and catalyze the biosynthesis of limonene, an important precursor of essential oils from the genus Mentha. This study provides useful information for the biosynthesis of terpenoids in the genus Mentha.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The Cosmic Evolution of C IV Absorbers at 1.4 < z < 4.5: Insights from 100,000 Systems in DESI Quasars

We present the largest catalog to date of triply ionized carbon (C IV ) absorbers detected in quasar spectra from the Dark Energy Spectroscopic Instrument. Using an automated matched-kernel convolution method with adaptive signal-to-noise thresholds, we identify 101,487 C IV systems in the redshift range 1.4 < z < 4.5 from 300,637 quasar spectra. Completeness is estimated via Monte Carlo simulations, and the catalog is 50% complete at EW C IV ≥ 0.4 Å. The differential equivalent width frequency distribution declines exponentially and shows weak redshift evolution. The absorber incidence per unit comoving path increases by a factor of 2–5 from z ≈ 4.5 to z ≈ 1.4, with stronger redshift evolution for strong systems. Using column densities derived from the apparent optical depth method, we constrain the cosmic mass density of C IV , Ω C IV , which increases by a factor of ∼3.8 from (0.82 ± 0.05) × 10 −8 at z ≈ 4.5 to (3.16 ± 0.2) × 10 −8 at z ≈ 1.4. From Ω C IV , we estimate a lower limit on intergalactic medium metallicity ${\mathrm{log}}({Z}_{{\rm{IGM}}}/{Z}_{\odot })\gtrsim -3.25$ at z ∼ 2.3, with a smooth decline at higher redshifts. These trends trace the cosmic star formation history and He II photoheating rate, suggesting a link between C IV enrichment, star formation, and UV background over ∼3 Gyr. The catalog also provides a critical resource for future studies connecting circumgalactic metals to galaxy evolution, especially near cosmic noon.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A distributed temperature profiling system for vertically and laterally dense acquisition of soil and snow temperature

Abstract. Measuring soil and snow temperature with high vertical and lateral resolution is critical for advancing the predictive understanding of thermal and hydro-biogeochemical processes that govern the behavior of environmental systems. Vertically resolved soil temperature measurements enable the estimation of soil thermal regimes, frozen-/thawed-layer thickness, thermal parameters, and heat and/or water fluxes. Similarly, they can be used to capture the snow depth and the snowpack thermal parameters and fluxes. However, these measurements are challenging to acquire using conventional approaches due to their total cost, their limited vertical resolution, and their large installation footprint. This study presents the development and validation of a novel distributed temperature profiling (DTP) system that addresses these challenges. The system leverages digital temperature sensors to provide unprecedented, finely resolved depth profiles of temperature measurements with flexibility in system geometry and vertical resolution. The integrated miniaturized logger enables automated data acquisition, management, and wireless transfer. A novel calibration approach adapted to the DTP system confirms the factory-assured sensor accuracy of ±0.1 ∘C and enables improving it to ±0.015 ∘C. Numerical experiments indicate that, under normal environmental conditions, an additional error of 0.01 % in amplitude and 70 s time delay in amplitude for a diurnal period can be expected, owing to the DTP housing. We demonstrate the DTP systems capability at two field sites, one focused on understanding how snow dynamics influence mountainous water resources and the other focused on understanding how soil properties influence carbon cycling. Results indicate that the DTP system reliably captures the dynamics in snow depth and soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes. Overall, the DTP system fulfills the needs for data accuracy, minimal power consumption, and low total cost, enabling advances in the multiscale understanding of various cryospheric and hydro-biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Study on Emulsification/Demulsification Behavior and Mechanism of Produced Liquid from Polymer Flooding on Alaska North Slope

Heavy oil reservoirs on Alaska North Slope (ANS) are unconsolidated and contain abundant clay minerals, where the first-ever field pilot is currently implemented to validate the use of polymer floods for heavy oil enhanced oil recovery (EOR). The polymer molecules and/or fine clay particles carried with the produced liquid could potentially affect the oil/water separation, which is one of the major concerns for field operators. This dissertation aims to investigate the emulsification behavior of produced liquid, understand the emulsifying mechanism, and seek an adaptive and cost-effective method to treat the produced liquid from polymer flooding. Emulsions were prepared by mechanically mixing the actual heavy oil and the produced water from the pilot site, of which the stability was investigated by bottle test method or multiple light scattering method. Drop size distribution and interfacial properties were measured via microscope and pendant drop technique to probe the stability mechanism further. Results showed that oil-continuous or water-continuous emulsion could be generated depending on the water cut, clay types, clay concentration, and polymer concentration. In the crude oil/water system, the increasing water cut triggered the phase inversion of oil-continuous emulsion to water-continuous emulsion, resulting in faster separation and lower emulsion stability. Whereas, clay particles, no matter added to the oil or water phase, resulted in an unfavorable phase inversion from the loose water-continuous emulsion to the tight oil-continuous emulsion as clay concentration increased. For all four types of clay except Ca-montmorillonite, clay particles added to water led to an earlier phase inversion and higher emulsion stability than that added to the oil. The dual function of polymer on emulsion stability was observed. On the one hand, both sheared and unsheared polymer tended to convert the oil-continuous emulsion formed in either crude oil/water system or complex crude oil/water/clay particle system to the water-continuous emulsion, acting as a weak demulsifier to accelerate the oil/water separation. On the other hand, the addition of polymer to the water-continuous emulsion could result in enhanced emulsion stability, which is primarily attributed to the increased viscosity of the continuous phase and the decreased drop size of the dispersed oil phase. Particularly, the sheared polymer had a weaker ability to stabilize the o/w emulsion than the unsheared polymer due to the lower viscosity of the sheared polymer solution resulting from the breakdown of the polymer macromolecules. As for the chemical demulsification tests, the performance of demulsifiers showed a complex dependency upon the water cut, the shearing intensity, demulsifier type and dosage, and the polymer concentration. A compound emulsion breaker, E12+E18, exhibited the most satisfactory demulsification performance despite the varied test conditions. For severe water-continuous emulsions that might require a multi-fold dosage of demulsifier, a less expensive electrolyte, KCl, was proposed to be used in combination with demulsifier E12+E18 to improve the demulsification performance. In the proposed demulsifier formula, the effectiveness of the commercial demulsifier relied on its destructive effect on the interfacial film, while the efficacy of KCl was mainly dependent on its viscosity reduction effect on the continuous phase. This dissertation illustrates that intermediate layer elimination and water clarification are the major challenges for produced liquid treatment from polymer flooding. It also provides practical and theoretical guidance in advance for the demulsification strategy of the produced liquid from the ongoing first-ever polymer flooding pilot on ANS.

Chang, Hongli↗
DOE OSTI2021

Data-Driven Adaptive Damping Controller for Wind Power Plants with Doubly-Fed Induction Generators

This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.

damping controller↗
DOE OSTI2025

Dynamical Sketching for Enhanced Communication Efficiency in Federated Learning

Federated learning (FL) has revolutionized distributed machine learning by enabling collaborative model training without sharing local data. However, communication efficiency and privacy guarantees remain significant challenges. This paper introduces a dynamic sketching mechanism in FL, optimizing the trade-off between communication efficiency and model accuracy. By dynamically selecting the sketch matrix size, our approach adapts to the evolving characteristics of the data and the model, ensuring optimal performance across diverse scenarios. We leverage Bayesian optimization to systematically tune the sketch parameters, achieving an effective balance between resource efficiency and model performance. Experimental results on the MNIST dataset using a convolutional neural network (CNN) architecture validate the proposed method's efficiency and scalability. Our dynamic sketching approach significantly outperforms fixed-size sketching techniques, achieving higher compression ratios (up to 62x) and providing better privacy guarantees while maintaining high model accuracy. These findings highlight the robustness and versatility of our approach and make it a valuable solution for privacy-preserving, communication-efficient federated learning.

Afrose, Sharmin [ORNL]↗
DOE OSTI2020

Understanding Impacts of Data Integrity Attacks on Transactive Control Systems

With the rapid growth of internet-connected smart devices capable of exchanging energy price information and adaptively controlling energy consumption of connected loads, the role of transactive control is expected to become more prominent in the modern grid. Transactive control systems integrate the wholesale and retail energy markets, and enable active participation of end users, thereby playing a key role in managing the rising number of distributed assets in the smart grid. The use of internet for the communication of data between the controllers at the building, distribution, and transmission levels makes the system susceptible to cyber-attacks. A skilled adversary can potentially manipulate the exchanged data with the intention of inflicting damage to the system. In this paper, four categories of metrics are put forth for evaluating the performance of the system when under data integrity attacks. A model for scaling-based data integrity attack has been described, and co-simulations have been performed on a 240 bus WECC transmission system model with detailed modeling of distribution systems at specific buses. Our results show that scaling-based data integrity attacks can have non-trivial impacts on the operational, financial, and comfort aspects of the transactive control system.

Smart grid, transactive control system, Buildings-↗
DOE OSTI2025

$\gamma$-ray angular correlations, distributions and linear polarization in tracking arrays

With $\gamma $-ray tracking arrays, the angular correlation and, especially, the linear polarization of $\gamma $ rays can be measured with high precision. However, because of the complexity of these spectrometers, measuring angular distributions is more involved. The techniques and associated formalisms were developed and established in the 1950s. The experimental setups of that era were relatively simple when compared to the advanced $\gamma $-ray tracking arrays available today. This paper aims to review and refine these techniques, unify the nomenclatures and, specifically, adapt them for use with the newest tracking arrays. In addition, new methods for producing the required response functions for these arrays are introduced.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A Generative Model for Realistic Galaxy Cluster X-Ray Morphologies

Abstract The X-ray morphologies of clusters of galaxies display significant variations, reflecting their dynamical histories and the nonlinear dependence of X-ray emissivity on the density of the intracluster gas. Qualitative and quantitative assessments of X-ray morphology have long been considered a proxy for determining whether clusters are dynamically active or “relaxed.” Conversely, the use of circularly or elliptically symmetric models for cluster emission can be complicated by the variety of complex features realized in nature, spanning scales from megaparsecs down to the resolution limit of current X-ray observatories. In this work, we use mock X-ray images from simulated clusters from The Three Hundred project to define a basis set of cluster image features. We take advantage of the clusters’ approximate self-similarity to minimize the differences between images before encoding the remaining diversity through a distribution of high-order polynomial coefficients. Principal component analysis then provides an orthogonal basis for this distribution, corresponding to natural perturbations from an average model. This representation allows novel, realistically complex X-ray cluster images to be easily generated, and we provide code to do so. The approach provides a simple way to generate training data for cluster image analysis algorithms and could be straightforwardly adapted to generate clusters displaying specific types of features or selected by physical characteristics available in the original simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil

Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.

58 GEOSCIENCES↗